Di Song

1.4k total citations
61 papers, 807 citations indexed

About

Di Song is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Di Song has authored 61 papers receiving a total of 807 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Pulmonary and Respiratory Medicine, 11 papers in Radiology, Nuclear Medicine and Imaging and 10 papers in Molecular Biology. Recurrent topics in Di Song's work include Cerebrovascular and Carotid Artery Diseases (8 papers), Glaucoma and retinal disorders (7 papers) and Cardiovascular Health and Disease Prevention (6 papers). Di Song is often cited by papers focused on Cerebrovascular and Carotid Artery Diseases (8 papers), Glaucoma and retinal disorders (7 papers) and Cardiovascular Health and Disease Prevention (6 papers). Di Song collaborates with scholars based in China, United States and United Kingdom. Di Song's co-authors include Jessie L.‐S. Au, M. Guillaume Wientjes, Jian‐Yong Shao, Hui Wang, Jie Wang, Bo Yang, Danny Z. Chen, Fei Xu, Yanping Kuang and Lulu Zhang and has published in prestigious journals such as The Journal of Immunology, Scientific Reports and The FASEB Journal.

In The Last Decade

Di Song

55 papers receiving 795 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Di Song China 15 224 164 160 136 136 61 807
Tao Xia China 16 191 0.9× 83 0.5× 233 1.5× 109 0.8× 204 1.5× 60 765
Yongdong Liu China 17 345 1.5× 158 1.0× 131 0.8× 71 0.5× 74 0.5× 64 882
Uroš Potočnik Slovenia 17 266 1.2× 242 1.5× 237 1.5× 105 0.8× 183 1.3× 87 1.0k
Karen Oliva Australia 18 451 2.0× 97 0.6× 320 2.0× 140 1.0× 128 0.9× 34 1.1k
Rashmi Kaul India 17 278 1.2× 119 0.7× 152 0.9× 77 0.6× 69 0.5× 58 1.0k
Chi‐Long Chen Taiwan 20 246 1.1× 81 0.5× 262 1.6× 181 1.3× 204 1.5× 49 947
Karen Bräutigam Germany 14 345 1.5× 338 2.1× 171 1.1× 105 0.8× 132 1.0× 32 916
Vinícius de Lima Vazquez Brazil 18 363 1.6× 107 0.7× 311 1.9× 85 0.6× 156 1.1× 47 882
Anna Haemel United States 14 259 1.2× 347 2.1× 224 1.4× 102 0.8× 78 0.6× 40 1.0k
Ibrahim Khalifeh Lebanon 20 311 1.4× 103 0.6× 357 2.2× 117 0.9× 126 0.9× 62 1.3k

Countries citing papers authored by Di Song

Since Specialization
Citations

This map shows the geographic impact of Di Song's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Di Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Di Song more than expected).

Fields of papers citing papers by Di Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Di Song. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Di Song. The network helps show where Di Song may publish in the future.

Co-authorship network of co-authors of Di Song

This figure shows the co-authorship network connecting the top 25 collaborators of Di Song. A scholar is included among the top collaborators of Di Song based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Di Song. Di Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yan, Hengyu, Mulong Du, Jianping Ding, et al.. (2024). Pan-Genome-Wide Investigation and Co-Expression Network Analysis of HSP20 Gene Family in Maize. International Journal of Molecular Sciences. 25(21). 11550–11550.
2.
Song, Di & Liwen Wang. (2024). Cost-utility analysis of treating mild stage normal tension glaucoma by surgery in China: a decision-analytic Markov model. Cost Effectiveness and Resource Allocation. 22(1). 13–13.
3.
Hong, Shaofu, et al.. (2024). Evaluation of Turbulence Index and Flow Pattern for Atherosclerotic Carotid Stenosis: A High-Frame-Rate Vector Flow Imaging Study. Ultrasound in Medicine & Biology. 50(4). 549–556. 1 indexed citations
4.
Hong, Shaofu, Di Song, Yigang Du, et al.. (2023). Feasibility Study of Combining Wall Shear Stress and Elastography to Assessthe Vascular Status of Carotid Artery. Current Medical Imaging Formerly Current Medical Imaging Reviews. 20. e270323214999–e270323214999. 1 indexed citations
5.
Song, Di, Ming Chen, Song Bai, et al.. (2022). Development and Validation of a Nomogram for Prediction of the Risk of MAFLD in an Overweight and Obese Population. Journal of Clinical and Translational Hepatology. 0(0). 0–0. 5 indexed citations
6.
Chen, Jing, Chen Cui, Huaiyu Wu, et al.. (2022). Feasibility of using AI to auto-catch responsible frames in ultrasound screening for breast cancer diagnosis. iScience. 26(1). 105692–105692. 5 indexed citations
7.
Song, Di, et al.. (2022). Blood Flow Turbulence Quantification of Carotid Artery With a High‐Frame Rate Vector Flow Imaging. Journal of Ultrasound in Medicine. 42(2). 427–436. 9 indexed citations
8.
Xu, Fei, Lulu Zhang, Wenting He, et al.. (2021). The Diagnostic Value of Serum PIVKA-II Alone or in Combination with AFP in Chinese Hepatocellular Carcinoma Patients. Disease Markers. 2021. 1–9. 23 indexed citations
9.
Song, Di, et al.. (2021). Diagnostic performance of elastography for breast non-mass lesions: A systematic review and meta-analysis. European Journal of Radiology. 144. 109991–109991. 9 indexed citations
10.
Huang, Mengyao, et al.. (2020). Risk stratification for nasopharyngeal carcinoma: a real-world study based on locoregional extension patterns and Epstein-Barr virus DNA load. Therapeutic Advances in Medical Oncology. 12. 3863547092–3863547092. 19 indexed citations
11.
Zhang, Lulu, Fei Xu, Wenting He, et al.. (2020). Development and validation of a prognostic nomogram for the pre-treatment prediction of early metachronous metastasis in endemic nasopharyngeal carcinoma: a big-data intelligence platform-based analysis. Therapeutic Advances in Medical Oncology. 12. 3863593172–3863593172. 8 indexed citations
12.
Wang, Jing, Pengfei Kong, Haiyun Wang, et al.. (2020). Identification of a Gene-Related Risk Signature in Melanoma Patients Using Bioinformatic Profiling. Journal of Oncology. 2020. 1–13. 13 indexed citations
13.
14.
Song, Di, et al.. (2019). Comparison of Refractive Measures of Three Autorefractors in School-Aged Children and Adolescents. Chinese Journal of Optometry & Ophthalmology. 21(10). 721–726.
15.
Yang, Xiaodi, Zhi-Yong Tao, Cheng Yang, et al.. (2017). [Component analysis of excretory/secretory protein from Trichinella spiralis adult worm].. PubMed. 35(1). 24–9. 4 indexed citations
16.
Wang, Jie, Di Song, Guangjian Lu, et al.. (2017). HLA-DMB restricts human T-cell leukemia virus type-1 (HTLV-1) protein expression via regulation of ATG7 acetylation. Scientific Reports. 7(1). 14416–14416. 5 indexed citations
17.
18.
Moon, Hyoungjoon, et al.. (2008). Establishment of PCR and RT-PCR for porcine endogenous retrovirus detection. 2 indexed citations
19.
Song, Di, et al.. (1996). Binding of Taxol to Plastic and Glass Containers and Protein under in Vitro Conditions. Journal of Pharmaceutical Sciences. 85(1). 29–31. 66 indexed citations
20.
Song, Di & Jessie L.‐S. Au. (1996). Direct injection isocratic high-performance liquid chromatographic analysis of mitomycin C in plasma. Journal of Chromatography B Biomedical Sciences and Applications. 676(1). 165–168. 17 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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